Using Amazon ElastiCache for Redis

I plan to use Amazon ElastiCache for Redis. Someone who is using it to tell me about the administration of the Database under that data warehouse


if you want to use Redis fully managed solution then check here:

Amazon elasticache offers a variety of tools and benefits:

multimedia content for Redis offers agile in-memory data storage to support live streaming use cases, this metadata storage can easily be used for user records and viewing histories.

Besides this, it also offers session storage, ideal for storing and managing session information, such as user authentication tokens. it’s easy to use Elasticache as a fast key value store with proper TTL in session keys to manage session information.


-Extreme Performance
-Fully managed and hardened
-Compatible with Redis
-Easily scalable
-Security and Compliance

What is Redis Bloom Fitter Pattern


Bloom filters are an interesting probabilistic data structure that have can be used to see if an item has never been added previously

Bloom filters work by running an item through a quick hashing function and sampling bits from that hash and setting them from a 0 to 1 at particular interval in a bitfield. To check for existence in a Bloom filter, the same bits are sampled. Many item may have bits that overlap, but since a hashing function produce unique identifiers, if a single bit from the hash is still a 0, then we know it has not been previously added.

A good use case for a Bloom filter is to check for an already used username. On a small scale, this is no problem, but as a service grows, this can be very taxing on a database. It is very simple to implement this with a ReBloom.

First, let’s add a handful of usernames as a test:

>  usernames funnyfred 
(integer) 1 
> BF.ADD usernames fredisfunny 
(integer) 1 
> BF.ADD usernames fred 
(integer) 1 
> BF.ADD usernames funfred 
(integer) 1

Now, let’s run some test versus the Bloom filter.

> BF.EXISTS usernames fred 
(integer) 1 
> BF.EXISTS usernames fred_is_funny 
(integer) 0

As expected, fred_is_funny yields a 0. A response of zero means we can be sure that this username has not been used. A response of 1 means it might have been used. We can’t say for certain as it might a case of overlapping bits between multiple items.

If we talk about use cases, Amazon ElastiCache is an excellent option for analytical and transactional processing in real time.


-Queues: amazon Elasticache offers a data structure in lists, this facilitates the implementation of a light and persistent queue. The lists offer atomic operations, blocking capabilities, this is very practical for applications that require a message agent.

-Machine Learning: provides agile in-memory data storage to create and implement Machine Learning models. It can be used to detect fraud in gambling and financial services.

-Geospatial analysis: you can use Amazon ElastiCache to add characteristics based on Geographical locations, such as driving time, distance traveled, in a few words it offers us a data structure in memory and custom operators to manage geospatial data at scale and with speed.